The formation of calcium carbonate (CaCO3) (i.e. scale) in potable water systems has long been a concern in water treatment and distribution. A literature review reveals that CaCO3 scaling issues are re-emerging due to climate change, temperature increases in hot water systems and lower use of scaling and corrosion inhibitors. Moreover, we have gathered insights that suggest CaCO3 coatings can be beneficial and stop pipeline leaks via self-repair or clogging. Ironically, the actions we are taking to increase the lifespan of distribution systems (i.e. adding corrosion inhibitors) might have worsened leaks and pipe lifespans due to interference with self-repair. The increasing occurrence of scaling coupled with gaps in knowledge over CaCO3 formation in water systems make revisiting this topic timely. The concept of autogenous repair by clogging with inert particles was examined using silica and alumina. Small 250 m diameter pinhole leaks were simulated in bench-scale water recirculation systems. Silica and alumina particles were added to solutions ranging from high to low ionic strength to determine the impact of water quality on leak repair. Size distribution and zeta potential of the particles were measured. Silica particles were practically unchanged by the different solution chemistries while the size and zeta potential of alumina particles varied. The rate of clogging with silica particles was not impacted by water chemistry. Alumina particles with a positive charge clogged 100% of the leaks while negatively charged alumina could not clog 100%. Very small alumina particles (4.1 m) stayed suspended but were unable to clog leaks. / Master of Science

In many drinking water systems in the United States, disinfectant is added to water as it leaves the plant to maintain a residual concentration in the distribution system. The disinfectant residual is maintained to inactivate contamination that enters the distribution system, to control biofilms, and to act as a sentinel for contamination in the distribution system. A model was developed to evaluate the potential effectiveness of the disinfectant residual at inactivating contamination. The model was used to examine contamination of a hypothetical distribution system through backpressure at a cross-connection under different operating conditions. The dilution and pathway of the hypothetical contaminant were examined as the contaminant moved through the system. Disinfection and inactivation kinetic relationships were used to model the inactivation of the contaminant in the system by the amount of disinfectant present. The model showed that both chlorine and chloramines in each decay and inactivation condition considered provided some benefit over no disinfectant at all when examining susceptible organisms. Chlorine, under medium and low decay conditions, provided the best inactivation. Where 29.8% of total node time steps received a contamination of concern in the absence of disinfectant residual, as low as 4.8% of total node time steps received a contamination of concern in the presence of disinfectant residual. Chloramines was found to persist longer in the distribution system, but resulted in much lower inactivation compared to chlorine. Disinfectant doses typical of common distribution system operation were able to reduce the impact of contamination once it entered the distribution system but, except for four cases, were unable to prevent contamination from spreading within the distribution system. Therefore, it was concluded that presence of a disinfectant residual will reduce the total number of exposure opportunities from a contamination event, but cannot be relied upon to eliminate the chance of exposure resulting from contamination. / Master of Science

Large public water utilities currently are required to take several 100 mL water samples every month in their distribution systems and to test these samples for the presence of total coliforms to comply with the Total Coliform Rule. How and where they take these samples is not specified. The Total Coliform Rule is currently undergoing review and revision. One possible revision is more specific rule language or guidance of where and when utilities take their monthly coliform water samples. This project considers various drinking water distribution system monitoring strategies for a large drinking water utility using simulations within an EPANET computer model of that utility's distribution system. A review of the literature and the use of best professional judgment help to inform the understanding of the primary causes of the occurrence of coliform bacteria in drinking water distribution systems. In this analysis, both contamination scenarios and coliform monitoring approaches are simulated in the EPANET computer model to better understand what types of contamination events might be detected by routine coliform monitoring and to what extent monitoring strategies affect observed results. In addition, statistical strengths of the various strategies and their respective results are considered in this project. Analysis of model output supports the assertion that water age may be a good factor to consider in designing a monitoring plan, especially if sampling cannot be conducted every day and that taking samples immediately after and in the vicinity of rapid changes in flow (e.g., during a firefighting incident) may help utility operators to better understand what associated risk, if any, exists to consumers of drinking water as a result of these flow conditions. / Master of Science

This thesis describes the application of microprocessor based relays with internet communication capabilities in distribution protection systems. The traditional distribution protection system (recloser, sectionalizers) was configured to automatically isolate faulted circuits as well as to reenergize unfaulted loads after a certain number of reclosing operations. Internet Peer-to-Peer communication enables distribution relays to communicate with others connected to the communication network without having a master device. According to the results, the addition of peer-to-peer communication to a traditional distribution protection system significantly enhances its general performance eliminating undesired losses of unfaulted load. Additionally, it reduces outage duration as well as thermal and mechanical stress due to successive re-energizations under faults condition. / Master of Science

High-impedance faults (HIFs) on distribution feeders are abnormal electrical conditions that cannot be detected by conventional protection schemes. These faults pose a threat on human lives when neighboring objects become in contact with the line's bare and energized conductors. An accurate electrical model for a HIF is implemented to investigate typical patterns in the line's current that allow for the detection of these faults. The occurrence of HIFs is detected with harmonic-current phase analysis and localized with recloser-sectionalizer technology as presented in this work. A sectionalizer algorithm is then presented showing the decision criteria for HIF declaration and shown to discriminate against nominal behavior in distribution feeders of similar harmonic content. Finally, it is shown that the algorithm will not produce a misreading when a current transformer enters saturation. / Master of Science

Yes / Distributed generators (DGs) are a reliable solution to supply economic and reliable electricity to customers. It is the last stage in delivery of electric power which can be defined as an electric power source connected directly to the distribution network or on the customer site. It is necessary to allocate DGs optimally (size, placement and the type) to obtain commercial, technical, environmental and regulatory advantages of power systems. In this context, a comprehensive literature review of uncertainty modeling methods used for modeling uncertain parameters related to renewable DGs as well as methodologies used for the planning and operation of DGs integration into distribution network. / This work was supported in part by the SITARA project funded by the British Council and the Department for Business, Innovation and Skills, UK and in part by the University of Bradford, UK under the CCIP grant 66052/000000.

In electricity markets, capacity cost must be determined in order to make capacity trading. In this thesis, capacity cost and the factors deriving the capacity cost are studied. First, fixed capacity cost of power plants is examined. Direct and indirect costs of fixed capacity cost are detailed with respect to different types of power plants and the impact of these factors to the capacity cost is given. Second, interconnection and system utilization costs of transmission and distribution system are considered in order to simulate energy flow from the producer to the customer. Finally, a capacity cost calculation program is practiced. By the help of this program, capacity cost of power plants is figured out, different cases are compared and the main factors affecting the capacity cost are discussed in detail.

No description available.

The increasing penetration of proactive agents in distribution systems (DS) has opened new possibilities to make the grid more resilient and to increase participation of responsive loads (RL) and non-conventional generation resources. On the resiliency side, plug-in hybrid electric vehicles (PHEV), energy storage systems (ESS), microgrids (MG), and distributed energy resources (DER), can be leveraged to restore critical load in the system when the utility system is not available for extended periods of time. Critical load restoration is a key factor to achieve a resilient distribution system. On the other hand, existing DERs and responsive loads can be coordinated in a market environment to contribute to efficiency of electricity consumption and fair electricity tariffs, incentivizing proactive agents' participation in the distribution system. Resiliency and market applications for distribution systems are highly complex decision-making problems that can be addressed using modern optimization techniques. Complexities of these problems arise from non-linear relations, integer decision variables, scalability, and asynchronous information. On the resiliency side, existing models include optimization approaches that consider system's available information and neglect asynchrony of data arrival. As a consequence, these models can lead to underutilization of critical resources during system restoration. They can also become computationally intractable for large-scale systems. In the market design problem, existing approaches are based on centralized or computational distributed approaches that are not only limited by hardware requirements but also restrictive for active participation of the market agents. In this context, the work of this dissertation results in major contributions regarding new optimization algorithms for market design and resiliency improvement in distribution systems. In the DS market side, two novel contribution are presented: 1) A computational distributed coordination framework based on bilateral transactions where social welfare is maximized, and 2) A fully decentralized transactive framework where power suppliers, in a simultaneous auction environment, strategically bid using a Markowitz portfolio optimization approach. On the resiliency side, this research proposed a system restoration approach, taking into account uncertain devices and associated asynchronous information, by means of a two-module optimization models based on binary programming and three phase unbalanced optimal power flow. Furthermore, a Reinforcement Learning (RL) method along with a Monte Carlo tree search algorithm has been proposed to solve the scalability problem for resiliency enhancement. / Doctor of Philosophy / Distribution systems (DS) are evolving from traditional centralized and fossil fuel generation resources to networks with large scale deployment of responsive loads and distributed energy resources. Optimization-based decision-making methods to improve resiliency and coordinate DS participants are required. Prohibitive costs due to extended power outages require efficient mechanisms to avoid interruption of service to critical load during catastrophic power outages. Coordination mechanisms for various generation resources and proactive loads are in great need. Existing optimization-based approaches either neglect the asynchronous nature of the information arrival or are computationally intractable for large scale system. The work of this dissertation results in major contributions regarding new optimization methods for market design, coordination of DS participants, and improvement of DS resiliency. Four contributions toward the application of optimization approaches for DS are made: 1) A distributed optimization algorithm based on decomposition and best approximation techniques to maximize social welfare in a market environment, 2) A simultaneous auction mechanism and portfolio optimization method in a fully decentralized market framework, 3) Binary programming and nonlinear unbalanced power flow, considering asynchronous information, to enhance resiliency in a DS, and 4) A reinforcement learning method together with an efficient search algorithm to support large scale resiliency improvement models incorporating asynchronous information.

The main aim of the study was to analyse the impact of physico-chemical parameters on drinking water quality, biofilm formation and antibiotic resistant bacteria in the drinking water distribution system in Mafikeng, North West Province, South Africa. Another objective was to isolate and characterise Pseudomonas and Aeromonas species from drinking water distribution system and detect the virulence gene determinants in the isolates by PCR analysis. The physico-chemical data obtained were subjected to statistical analysis using Excel 2007 (Microsoft) and SPSS (version 14.0) programmes. Pearson’s correlation product of the moment was used to determine the correlation between EC, TDS, pH and temperature. The two tailed test of significance (p<0.05) was used in order to determine the significance of the result. Antibiotic susceptibility tests were performed using Kirby-Bauer disk diffusion method. Cluster analysis based on the antibiotic inhibition zone diameter data of different organisms isolated from different sites was determined and was expressed as dendograms using Wards algorithm and Euclidean distance of Statistica version 7. Specific PCR was used to determine the identities of presumptive Pseudomonas and Aeromonas species through amplification of the gyrB, toxA and the ecfX gene fragments. Virulence gene determinants for the confirmed Pseudomonas and Aeromonas species were detected by amplifying the exoA, exoS and exoT genes and the aerA and hylH gene fragments, respectively. A Gene Genius Bio imaging system (Syngene, Synoptics; UK) was used to capture the image using GeneSnap (version 3.07.01) software (Syngene, Synoptics; UK) to determine the relative size of amplicons. Physico-chemical parameters were monitored from three drinking water sources three times a week and bacteriological quality was monitored weekly for four months from raw and treated drinking water. Water samples were analysed for pH, temperature, total dissolved solids (TDS) and electric conductivity (EC). Bacterial consortia from drinking water samples were isolated using selective media and enumerated. The results revealed a good chemical quality of water. However, the microbial quality of the water is not acceptable for human consumption due to the presence of Pseudomonas, Aeromonas, faecal coliforms (FC), total coliforms (TC) and Heterotrophic bacteria. The results showed that the drinking water is slightly alkaline with pH value ranging between7.7 to 8.32. What is of concern was the microbial quality of the water. Pseudomonas sp., faecal coliforms (FC), total coliforms (TC) and heterotrophic bacteria were present in some of the treated water samples. The most significant finding of this study is that all drinking water samples were positive for Pseudomonas sp.(>100/100ml), but also that when one considers the TDS it demonstrates that water from the Modimola Dam has an impact on the quality of the mixed water. The prevalence and antibiotic resistance profiles of planktonic and biofilm bacteria isolated from drinking water were determined. The susceptibility of these isolates was tested against 11 antibiotics of clinical interest and the multiple antibiotic resistance (MAR) patterns were compiled. The most prevalent antibiotic resistance phenotype observed was KF-AP-C-E-OT-K-TM-A. All isolates from all samples were susceptible to ciprofloxacin. However, all faecal coliforms and Pseudomonas spp. were susceptible to neomycin and streptomycin. On the contrary all organisms tested were resistant to erythromycin (100%) trimethoprim and amoxycillin. Cluster analysis based on inhibition zone diameter data could not differentiate the various isolated into sample types. The highest prevalence of antibiotic resistant isolates was observed in Modimola Dam and Molopo eye. Biofilms were investigated in both raw water and treated drinking water sources for the presence of faecal coliforms, total coliforms, Pseudomonas spp., Aeromonas spp. and heterotrophic bacteria based on conventional microbiology and molecular methods. Drinking water biofilms were grown twice and the biofilm developing device containing copper and galvanized steel coupons were utilized. The Mini Tap filter, a home water treatment device which can be used at a single faucet, under constant flow was used during the second collection of treated water samples from cold water taps. Scanning electron micrograph revealed the existence of biofilms in all the sites investigated and the highest density was obtained on galvanized steel coupons. Isolates were tested against the antibiotics ampicillin (10μg), cephalothin (5μg), streptomycin (10μg), erythromycin (15μg), chloramphenicol (30μg), neomycin (30 μg), amoxycillin (10 μg), ciprofloxacin (5 μg), trimethoprim (25μg), kanamycin (30μg), and oxytetracycline (30μg). The multiple antibiotic resistance profiles and the presence of virulence related genes were determined. Various types of drug resistance and presence of virulence genes were observed. The most prevalent resistance phenotype observed was KF-AP-C-E-OT-TM-A. In conclusion, the results indicated the occurrence of faecal indicator bacteria in the drinking water destined for human consumption. Faecal indicator bacteria are the major contributors of poor drinking water quality and may harbour opportunistic pathogens. This highlighted survival of organisms to treatment procedures and the possible regrowth as biofilms in plumbing materials. The detection of large proportion of MAR Aeromonas and Pseudomonas species which possessed virulent genes was a cause of concern as these could pose health risks to humans. The data obtained herein may be useful in assessing the health risks associated with the consumption of contaminated water. / PhD (Microbiology), North-West University, Potchefstroom Campus, 2014